We envision a world in which talk therapy can be given by a computer, exactly where and when it is needed. Recent advances in Natural Language Processing (NLP) and Deep Learning, have provided new ways to bring this vision to a reality.
The focus of the first project is to apply a known and structured therapeutic technique (Motivational Interviewing) to a specific problem in addiction (Smoking Cessation).
It is a collaboration with the Nicotine Dependence Clinic at the Centre for Addiction and Mental Health and with the iSchool at the University of Toronto.
The first prototype chatbot was developed by Fahad Almusharraf in his M.A.Sc. thesis the first part of which (describing the design of the bot) was published in this paper. This bot makes use of an NLP classifier to provide specific relevant reflections and responses to subjects who describe the reasons for and against smoking. The second paper (which describes the effect of the intervention) is in preparation.
That work provided a rich dataset of conversations that is being used as the basis for a more advanced bot, in which we would like to generate motivational-interviewing style reflections that are not pre-written, using zero shot, few shot generation, and fine-tuning techniques with transformer architectures. It it is related to the work on reflection generation from the University of Michigan.
Collaborators: Dr. Peter Selby, Head of the Nicotine Dependence Clinic, CAMH
Graduate Students: Fahad Almusharraf, Imtihan Ahmed, Ash Kumar, Mohamed Abdelwahab, Jiading Zhu
Undergraduate Students: Eric Keilty, Yanisa Khambanonda, Arnaud Deza, Marc Morcos, Avi Kraft, Vidya Sujaya, Leon Zhu, Angus Wang
The Edward S. Rogers Sr. Department of Electrical and Computer Engineering,
Faculty of Applied Science and Engineering, University of Toronto